Vulnerability CVE-2021-29522


Published: 2021-05-14

Description:
TensorFlow is an end-to-end open source platform for machine learning. The `tf.raw_ops.Conv3DBackprop*` operations fail to validate that the input tensors are not empty. In turn, this would result in a division by 0. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/a91bb59769f19146d5a0c20060244378e878f140/tensorflow/core/kernels/conv_grad_ops_3d.cc#L430-L450) does not check that the divisor used in computing the shard size is not zero. Thus, if attacker controls the input sizes, they can trigger a denial of service via a division by zero error. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

Type:

CWE-369

(Divide By Zero)

CVSS2 => (AV:L/AC:L/Au:N/C:N/I:N/A:P)

CVSS Base Score
Impact Subscore
Exploitability Subscore
2.1/10
2.9/10
3.9/10
Exploit range
Attack complexity
Authentication
Local
Low
No required
Confidentiality impact
Integrity impact
Availability impact
None
None
Partial
Affected software
Google -> Tensorflow 

 References:
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-c968-pq7h-7fxv
https://github.com/tensorflow/tensorflow/commit/311403edbc9816df80274bd1ea8b3c0c0f22c3fa

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